Python code to identify sources of chemical pollutants in waterways

This dataset contains python code to carry out source apportionment of chemicals in river water. Convex optimisation is used to efficiently apportion tracer and pollutant sources from point concentration observations. A minimum working example of the python code and the open-source framework used for the analysis is also provided. Chemical data collected in 2019-2020 along the River Wandle (Thames, UK) were used to test the code and example results are also included. The code assumes conservative mixing and hence is likely to be best suited to assessing chronic sources of pollution (i.e., sources that are temporally invariant, or as near as, during the sampling campaign). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/8ae3c419-611d-4bee-ad41-1c9081e79975

Identification info

Metadata Language: English (en)

Character set: utf8

Dataset Reference Date (): 2024-05-01

Identifier: https://catalogue.ceh.ac.uk/id/8ae3c419-611d-4bee-ad41-1c9081e79975

Identifier: doi: / 10.5285/8ae3c419-611d-4bee-ad41-1c9081e79975

Other citation details: Chrapkiewicz, K., Lipp, A., Barron, L., Barnes, R., Roberts, G. (2024). Python code to identify sources of chemical pollutants in waterways. NERC EDS Environmental Information Data Centre 10.5285/8ae3c419-611d-4bee-ad41-1c9081e79975

Imperial College London - Chrapkiewicz, K.

https://orcid.org/0000-0001-6949-9741

University of Oxford - Lipp, A.

https://orcid.org/0000-0003-2130-8576

Imperial College London - Barron, L.

https://orcid.org/0000-0001-5986-3853

Lawrence Berkeley National Laboratory - Barnes, R.

Imperial College London - Roberts, G.

https://orcid.org/0000-0002-6487-8117

Imperial College London - Gareth Roberts

Imperial College London

NERC EDS Environmental Information Data Centre

GEMET - INSPIRE themes, version 1.0 ()

Environmental Monitoring Facilities

Limitations on Public Access: otherRestrictions

Other constraints: no limitations

Use constraints: otherRestrictions

Other constraints: This resource is available under the terms of the Open Government Licence

Use constraints: otherRestrictions

Other constraints: If you reuse this data, you should cite: Chrapkiewicz, K., Lipp, A., Barron, L., Barnes, R., Roberts, G. (2024). Python code to identify sources of chemical pollutants in waterways. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/8ae3c419-611d-4bee-ad41-1c9081e79975

Topic category

Environment

Distribution Information

Data format

Python ()
Comma-separated values (CSV) ()
NetCDF (.nc) ( 4 )
GeoTIFF (.tif) ()
Portable Network Graphics (.png) ()
.yaml ()

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Resource Locator: Supporting information
Supporting information available to assist in re-use of this dataset

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Resource Locator: Supporting information
Supporting information available to assist in re-use of this dataset

Quality Scope: nonGeographicDataset

Other: nonGeographicDataset

Report

Dataset Reference Date (): 2010-12-08

Statement: The code was developed as part of a six-month project funded via a NERC Exploring the Frontiers grant. K. Chrapkiewicz was the principal code developer with A. Lipp. We made use of existing models developed by co-investigators A. Lipp and R. Barnes. This work built upon the optimisation techniques developed by A. Lipp, G. Roberts and colleagues. The data inverted in this study were generated L Barron and colleagues (Egli et al., 2023). To run the code please see the readme files that accompany this repository. Briefly, once the code is downloaded and installed a minimum working example can be run using > python examples/mwe.py. Examples of data and their associated formats are included with this repository. The raw chemical data are also included. Examples of outputs in the form of figures (.png format) are also included. With regards to quality assurance, a synthetic data inversion was conducted and an Analysis of Variance and an assessment of the uncertainties were also carried out. Further details are provided in the supporting documentation and cited papers.

Metadata

File identifier: 8ae3c419-611d-4bee-ad41-1c9081e79975 XML

Metadata Language: English (en)

Character set: ISO/IEC 8859-1 (also known as Latin 1)

Resource type: nonGeographicDataset

Hierarchy level name: nonGeographicDataset

Metadata Date: 2024-05-07T12:39:32

Metadata standard name: UK GEMINI

Metadata standard version: 2.3

NERC EDS Environmental Information Data Centre

Lancaster Environment Centre, Library Avenue, Bailrigg , Lancaster , LA1 4AP , UK

https://eidc.ac.uk/

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